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Duration 7 hours
Course Outline
Module 1: Introduction to Manus for Finance Professionals
- Understanding general AI agents: the cycle of planning, acting, and delivering versus simply answering.
- Chat mode vs. agent mode: determining the appropriate use case for each.
- Credit mechanics: understanding costs per task and the team’s shared credit pool.
- Interface overview: tasks, Projects, files, connectors, Skills, and Automations.
- Positioning Manus within finance, forensic, and corporate workflows, and identifying its limitations.
- Practical exercise: Execute a small task in both modes and compare results and credit consumption.
Module 2: Briefing, Steering, and Review Processes
- Crafting actionable briefs: defining goals, inputs, output formats, and constraints.
- Monitoring agent activity, intervening during tasks, and managing browser interactions and login steps.
- Evaluating outputs: verification checks, requesting sources, and deciding when to re-run tasks.
- Exercise: Conducting background and regulatory research on a target company.
- Exercise: Using Wide Research to compare multiple companies against specific criteria.
Module 3: Handling Financial Data
- Uploading various file types: spreadsheets, PDF statements, and finance system exports.
- Cleaning and standardizing ledgers; creating formulas and summaries in Excel-style output.
- Extracting specific figures from PDF financial statements into structured tables.
- Performing reconciliations and anomaly checks (e.g., duplicates, round-number tests, Benford's-law screening).
- Exercise (Forensic): Identify anomalies in a synthetic transaction ledger and document the methodology.
- Exercise (Corporate Finance): Construct a comparables table from provided statements.
Module 4: Final Deliverables and Workflow Repetition
- Generating memos, slide decks, and interactive dashboards from the same analytical data.
- Projects: Consolidating files, instructions, and context for specific clients or engagements.
- Skills: Converting successful workflows (e.g., due-diligence checklists, valuation templates) into reusable steps.
- Automations: Setting up scheduled or event-triggered tasks, such as weekly market summaries.
- Exercise: Package Module 3 analysis into a memo and slides, then save the methodology as a Skill.
Module 5: Risk, Governance, and Credit Management
- Data governance: Determining permissible data inputs based on firm policy, client confidentiality, and regulatory standards.
- Provider context: Understanding Manus’s 2025–26 ownership changes and the August 2026 data deletion policy, and their implications for data decisions.
- Output verification: Addressing hallucinations, outdated sources, and calculation errors through citation and spot-checking.
- Audit trails: Saving task histories, exporting outputs, and documenting agent actions.
- Credit discipline: Sizing tasks appropriately, using Chat mode for simple queries, and preventing uncontrolled credit usage.
- Discussion: Developing a one-page team usage policy.
Module 6: Capstone Project and Future Steps
- Participants develop a workflow tailored to their specific job functions.
- Brief presentation to the group, receiving feedback from the trainer and peers.
- Personal 30-day action plan: Identifying two tasks to migrate to Manus and one Skill to build.
- Takeaway materials: Prompt patterns, review checklists, and credit usage guides.
Requirements
- Basic proficiency with web applications is assumed; no prior AI experience is necessary.
- Participants must sign in to their individual Manus licenses on work laptops using Chrome or Edge. As Manus is a cloud-based service, no virtual machine is required.
- Please verify the Manus subscription tier and credit balance before the course begins. Ideally, schedule the training early in the billing cycle, as a full day of practical work may consume a significant portion of the team’s monthly credits.
- Confirm with IT which connectors (e.g., Gmail, Google Drive, Notion) are approved to ensure demonstrations align with post-course usage.
- The trainer utilizes a separate paid Manus account for preparation and live demonstrations.
- All exercise data is synthetic and provided by the trainer; participants should not bring client data.
- Pre-course survey (approximately 10 minutes): Participants should identify one or two repetitive tasks from their current roles and submit this at least one week prior to the course.
Target Audience
- Finance Associates
- Forensic Accountants
- Corporate Finance Professionals
Testimonials (4)
The difference between strategy and plan
Berat Rahmani - Wallee Group AG
Course - Leadership and Team Management for Managers
How to manage business financials
surprise mtileni - Hatima Holdings (Pty) ltd
Course - Learning Xero
Good communication, open for discussion, kept it interesting and engaging
Ahmet Keyman - Keytrade AG
Course - Management Accounting and Finance for Non-Finance Professionals
Experience of the trainer and his way of conveying the content
